self.docstore = docstore
        self.document: Optional[Document] = None
    def search(self, term: str) -> str:
        """Search for a term in the docstore, and if found save."""
        result = self.docstore.search(term)
        if isinstance(result, Document):
            self.document = result
            return self.document.summary
        else:
            self.document = None
            return result
    def lookup(self, term: str) -> str:
        """Lookup a term in document (if saved)."""
        if self.document is None:
            raise ValueError("Cannot lookup without a successful search first")
        return self.document.lookup(term)
[docs]class ReActTextWorldAgent(ReActDocstoreAgent, BaseModel):
    """Agent for the ReAct TextWorld chain."""
[docs]    @classmethod
    def create_prompt(cls, tools: Sequence[BaseTool]) -> BasePromptTemplate:
        """Return default prompt."""
        return TEXTWORLD_PROMPT
    @classmethod
    def _validate_tools(cls, tools: Sequence[BaseTool]) -> None:
        if len(tools) != 1:
            raise ValueError(f"Exactly one tool must be specified, but got {tools}")
        tool_names = {tool.name for tool in tools}
        if tool_names != {"Play"}:
            raise ValueError(f"Tool name should be Play, got {tool_names}")
[docs]class ReActChain(AgentExecutor):
    """Chain that implements the ReAct paper.
    Example:
        .. code-block:: python
            from langchain import ReActChain, OpenAI
            react = ReAct(llm=OpenAI())
    """
    def __init__(self, llm: BaseLLM, docstore: Docstore, **kwargs: Any):